## 2010 Primary Sulfur Dioxide (SO 2 

## )

National Ambient Air Quality Standard (NAAQS)

Technical Analyses and Information Supporting the

Designation Recommendation for Oklahoma

Modeling Compliance with the 1

- Hour SO 2 

## NAAQS

Modeling Report

Prepared by the Engineering Section of the Permitting Unit

Air Quality Division

Oklahoma Department of Environmental Quality

September 8 , 2015

### Table of Contents

1. WHAT IS THE BACKGROU ND FOR THE MODELING?

................................ ................ 1

1.1 Which sources are affected sources?

................................ ................................ .... 1

1.2 Which sources will shut down or have proposed to shut down?

....................... 2

1.2.1 What will happen to the GRDA Grand River Energy Center?

........... 2

1.2.2 What will happen to the PSO NE Power Station?

.............................. 2

1.3 Which sources were modeled?

................................ ................................ .............. 3

1.3.1 How was the OG&E Muskogee Generating Station modeled?

.......... 3

1.3.2 How was the OG&E Sooner Generating Station modeled?

............... 3

1.3.3 How was the WFEC Hugo Generating S tation modeled?

.................. 3

2. WHAT MODELING PROGRA MS WERE USED FOR THE MODELING

ANALYSIS?

................................ ................................ ................................ ........................... 3

2.1 What is the recommended air dispersion model?

................................ ............... 3

2.2 Was screening modeling used?

................................ ................................ ............. 4

3. HOW WERE THE MODELIN G DOMAINS ESTABLISHE D FOR THE MODELING

ANALYSES?

................................ ................................ ................................ .......................... 4

3.1 How were the modeling domains setup?

................................ .............................. 4

3.2 How were the receptor grids established?

................................ ........................... 5

3.3 What terrain data was utilized for the modeling analyses?

............................... 6

3.4 What were the domain classifications: rural or urban?

................................ ..... 6

4. WHAT SOURCE DATA WAS USED IN THE MO DELING ANALYSIS?

....................... 7

4.1 What are the affected source configurations and source types?

....................... 7

4.2 What nearby sources were included in the modeling domains?

....................... 7

4.3 How were intermittent emission sources addressed?

................................ ......... 7

4.4 What are the affected source emissions inputs?

................................ .................. 7

4.4.1 How were hourly emissions from the affected so urces

determined?

................................ ................................ ......................... 8

4.4.2 What operational data was used from the RATA?

............................. 8

4.5 How was GEP stack height addressed?

................................ ............................... 94.6 Was building downwash included in the modeling analyses?

........................... 9

5. WHAT METEOROLOGICAL DATA WAS USED IN THE MODELING

ANALYSIS?

................................ ................................ ................................ ........................... 9

5.1 What meteorological data was used?

................................ ................................ ... 9

5.2 What surface data was used?

................................ ................................ .............. 10

5.2.1 How were sites from the ISHD evaluated?

................................ ....... 10

5.2.2 What is Oklahoma Mesonet data and how is it used?

...................... 11

5.3 What upper air data was used?

................................ ................................ .......... 11

5.4 How were surface characteristics of the meteorological sites determined?

... 11

5.4.1 What was used to determine the surface moisture conditions?

........ 12

6. WHAT BACKGROUND MONI TORING DATA WAS USED IN THE MODELING

ANALYSES?

................................ ................................ ................................ ........................ 12

6.1 What background monitoring data is utilized?

................................ ................ 12

7. WHAT ARE THE MODELED FACILITY IMP ACTS?

................................ ..................... 13

7.1 What were the modeled impacts for the domain which included the

WFEC Hugo Generating Station?

................................ ................................ ...... 13

7.2 What were the modeled impacts for the domain which included the

OG&E Muskogee Generating Station?

................................ ............................. 13

7.3 What were the modeled impacts for the domain which included the

OG&E Sooner Generating Station?

................................ ................................ ... 16

8. WHAT IS THE SUMMARY OF THE MODELING RESU LTS?

................................ ...... 17

8.1 Wh at areas demonstrate compliance with the 2010 1

- hour SO 2 NAAQS

using modeling?

................................ ................................ ................................ .... 17

8.2 What areas do not currently demonstrate compliance with the 2010 1

-

hour SO 2 NAAQS using modeling?

................................ ................................ .... 17

8.2.1 What area has potential impacts greater than the 2010 1

- hour

S O 2 NAAQS that were predicted under Scenario 1 for the OG&E

Muskogee Generating Station?

................................ ......................... 18

9. WHAT REFERENCES WERE USED?

................................ ................................ ............... 18APPENDICES

APPENDIX A

– FACILITY DOMAINS WITH RECEPTORS

APPENDIX B

– LAND USE/LAND COVER AERIAL PHOTOS

APPENDIX C

– AERIAL PHOTO OVERLAID WITH FACILITY DATA

APPENDIX D

– SOURCE DATA

APPENDIX E

– 2012

- 2014 OKLAHOMA MESONET SITES & ASSOCIATED ISH & ESRL

STATIONS

APPENDIX F

– WIND ROSES

APPENDIX G

– SURFACE CHARACTERIST ICSOklahoma 2010 SO 2 NAAQS Modeling Report Page 1



### 1. WHAT IS THE BACKGROUND FOR THE MODELING?

On June 2 2 , 2010, the U.S. Environmental Protection Agency (EPA) revised the primary sulfur

dioxide (SO 2 ) National Ambient Air Quality Standard (NAAQS). T he EPA promulgated a new

1

- hour annual primary SO 2 standard at a level of 75 parts per billion (ppb) , based on the 3

- year

average of the annual 99 th percentile of the daily maximum 1

- hour average concentrations. The

area designation process typically relies on air quality concentrations characterized by ambient

monitoring data to identify areas that are either meeting or vio lating the relevant standard.

However, a hybrid approach using modeling and monitoring for the designation process was

proposed because of the following:

 SO 2 impacts are considered to be “ source

- oriented ” rather than “ regional ” ( peak

concentrations of SO 2 are commonly caused by one or a few major point sources in an area

and peak concentrations are typically observed relatively close to the source ) ;

 A mbient SO 2 concentrations can be modeled accurately using well understood air quality

modeling tools ; and

 Only a pproximately 35 % of the monitoring network w as addressing locations of maximum

(highest) concentrations of specific source s or group s of sources

.

On March 2, 2015, a Consent Decree (CD) was filed requiring the EPA to sign for publication in

the Fede ral Register no later than sixteen (16) months from March 2, 2015, a notice of EPA’s

promulgation of designations for the 2010 revised primary SO 2 NAAQS, pursuant to Section

107(d) of the CAA, and within ten (10) business days following such signature, del iver the

notice to the Office of the Federal Register for review and prompt publication, for undesignated

areas which:

1) B ased on air quality monitoring in the three (3) full calendar years preceding such deadline

have monitored violations of the 2010 revis ed primary SO 2 NAAQS; or

2) C ontain any stationary source that has not been “announced for retirement” by the date of

this Consent Decree, and that, according to the data in EPA’s Air Markets Database, either

a. E mitted more than 16,000 tons of SO 2 in 2012, or

b. E mitted more than 2,600 tons of SO 2 and had an annual average emission rate of 0.45

lbs SO 2 /MMBTU or higher in 2012.

By September 18 , 201 5

, the S tate of Oklahoma may submit to EPA additional information

regarding the affected facilities and for which updated air quality analyses have been used to

characterize the air quality around the source either through monitoring, modeling

, or a

combination of modeling and monitoring

.

1.1 Whic h s ources are a ffected s ources ?

Based on the consent decree , the following sources are the affected sources :Oklahoma 2010 SO 2 NAAQS Modeling Report Page 2 Table 1 .1

- 1

. Affected Sources

Company Facility /Emission Unit County 2012

Emissions

(TPY) Avg.

Emission Rate

(lb/MMBTU)

Oklahoma Gas and Electric Muskogee Generating

Station Muskogee 22,647

Unit 4 7,356 0.48

Unit 5 7,328 0.47

Unit 6 7,963 0.54

Oklahoma Gas and Electric Sooner Generating Station Noble 15,884

Unit 1 8,591 0.56

Unit 2 7,293 0.49

Western Farmers Electric

Coop Hugo Generating Station Choctaw

Unit 1 8,066 0.60

There were two other facilities Grand River Dam Authority (GRDA) Grand River Energy Center

(Unit 1) in Mayes county and Public Service Company (PSO) Northeast (Unit 3313 & Unit

3314) in Rogers County which had an average emissions rate greater than 0.45 lb/MMBTU but

which had “announced for retirement” the affected units at their facility prior to March 2, 2015.

1.2 Which sources will shut down or have proposed to shut down?

There are two f

acilities which are scheduled or anticipated to shut down or cease operations by

January 1, 2017 , or which will limit emissions to below the applicability threshold . These

facilities and their circumstances are s hown in S ections 1.2.1 and 1.2.2

.

1.2. 1 What will happen to the GRDA Grand River Energy Center ?

GRDA has proposed shutting down Unit No. 1 and reducing operation of Unit No. 2. The shut

down of Unit No. 1 should be completed by April 2016. Construction Permit No. 2009

- 179

- C

(M

- 3) was issued on August 21, 2014, authorizing the construction of a natural gas fired

combustion turbine , installation of activated carbon injection on Unit 2, and either shutting down

Unit No. 1 or conversion of Unit No. 1 to natu ral gas by the Mercury and Air Toxics Standards

( MATS ) compliance date of April 2016

. Therefore, Unit No. 1 was excluded from the

requirements of the CD. Unit 2’s average emission rate during 2012 was 0.2 lb/MMTBTU

which is why it was excluded

.

1.2. 2 Wh at will happen to the PSO NE Power Station?

PSO has proposed shutting down Unit No. 331 4 and reducing operation of Unit No. 331 3. Permit

No. 2009

- 179

- TVR (M

- 5) was issued on November 20, 2013, authorizing the installation of an

activated carbon injection s ystem on Unit 3313 and either shutting down Unit 3314 or

conversion of Unit No. 3314 to natural gas by the MATS compliance date of April 2016. The

shutdown of Unit No. 331 4 should be completed by April 2016. Therefore, Unit No. 3314 was

excluded from the requirements of the CD. By April 2016, Unit 3313 must meet emission limits

of 0.4 lb/MMBTU which is why it was excluded.Oklahoma 2010 SO 2 NAAQS Modeling Report Page 3

1.3 Which sources were modeled?

There are three affected facilities for which air dispersion modeling was conducted to determine

imp acts and to help with recommendations for the 2010 1

- hour SO 2 designations . These

facilities and their circumstances are shown in the following sections.

1. 3

. 1 How was the OG&E Muskogee Generating Station modeled ?

OG&E is required by the Regional Haze Pr ogram to install Best Available Retrofit Technology

(BART) on Unit 4 and Unit 5 (40 CFR § 52.1923) . OG&E has committed to meeting the federal

emission limit of 0.06 lb/MMBTU by January 4 , 201 9 , by conversion of Unit 4 and Unit 5 to

natural gas. Since the conversion will occur sometime in the future, the air quality analyses for

this facility involved three operating scenarios:

1) Modeling of current actual emissions for Unit 4, Unit 5, & Unit 6;

2) Modeling of Unit 4 using the BART emission limit and Unit 5 & Unit 6 using the

maximum actual emission rate during 2012 through 2014; and

3) Modeling of Unit 4 & Unit 5 using the BART emission limit & Unit 6 using the

maximum actual emission rate during 2012 through 2014.

1. 3

. 2 How was the OG&E Sooner Generating Station modeled ?

OG&E is required by the Regional Haze Program to install BART on Unit 1 and Unit 2 (40 CFR

§ 52.1923) . OG&E has committed to meeting the federal emission limit of 0.06 lb/MMBTU by

January 4 , 201 9 , by controlling Unit 1 and Unit 2 using f lue gas scrubbing or by converting the

units to natural gas. Since the emission reduction will occur sometime in the future, the air

quality analyses for this facility involved two operating scenarios:

1) Modeling of current actual emissions for Unit 1 & Uni t 2; and

2) Modeling of Unit 1 using the BART emission limit and Unit 2 using the maximum

actual emission rate during 2012 through 2014.

1. 3

. 3 How was the WFEC Hugo Generating Station modeled ?

WFEC is required to comply with 40 CFR Part 63, NESHAP, Subpart DDDDD and will install

an activated carbon injection (ACI) system by April 16, 2016. While there will be a small

reduction in SO 2 emissions resulting from the installation of the ACI , the air quality analys i s for

this facility only involve s one operating scenario:

1) Modeling of current actual emissions for Unit 1.



### 2. WHAT MODELING PROGRAMS W ERE USED FOR THE

MODELING ANALYSIS?

2 .1 What is the r ecommended a ir d ispersion m odel ?

Given the source

- oriented nature of SO 2 , dispersion models are appropriate air quality modeling

tools to predict the near

- field concentrations. For area designations under the 2010 1

- hour SO 2Oklahoma 2010 SO 2 NAAQS Modeling Report Page 4

primary NAAQS, the AMS/EPA Regulatory Model (AERMOD) w as used a s outlined in the

August 23, 2010

, clar ification memo, “Applicability of Appendix W Modeling Guidance for the

1

- hour SO 2 NAAQS

. ” AERMOD is the preferred air dispersion model , because it is capable of

handling rural and urban areas, flat and complex terrain, surface and elevated releases, and

m ultiple sources (including point, area, and volume sources), to address ambient impacts for the

designation s process.

The AERMOD modeling system includes the following components:

 AERMOD (Version 14134) : the dispersion model ;

 AERMAP (Version 11103) : the terrain processor for AERMOD ; and

 AERMET (Version 14134) : the meteorological data processor for AERMOD

.

Other components that may be used, depending on the application, are:

 BPIPPRIME (Version 04274) : the building input processor ;

 AERMINUTE (Version 14 3 37) : a 1

- minute Automated Surface Observing System ( ASOS )

winds pre

- processor to AERMET ;

 AERSURFACE (Version 13016) : the surface characteristics processor for AERMET ;

 AERSCREEN (Version 14147) : a screening version of AERMOD ;

2.2 W as s creening m odeling u sed?

Screening modeling analyses provide conservative estimates of source impacts with a minimum

of input. AERSCREEN is the screening model for AERMOD. AERSCREEN will produce

worst

- case estimates of 1

- hour impacts for a single source using default meteor ological data and

actual terrain data. Ambient impacts from natural gas fired sources were analyzed using

AERSCREEN to show that they do not have significant impacts within the domains and

scenarios modeled

.



### 3. HOW W ERE THE MODELING DOMAINS ESTABLISHED FOR THE

MODELING ANALYS E S?

3

. 1 How w ere the m odeling d omain s setup?

Domains were assigned to each facility. T he modeling domains are centered over the affected

sources. The following table shows the affected sources, assigned domains, and corresponding

Oklahoma Mesonet meteorological data site.

Table 3.1

- 1 Domain ID, Mesonet Site, & Affected Facility

ID Mesonet Site Company Facility

20 Hugo Western Farmers Electric Coop Hugo Generating Station

36 Porter Oklahoma Gas and Electric Muskogee Generating Station

39 Redrock Oklahoma Gas and Electric Sooner Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report Page 5

Based on EPA guidance, the general guideline for determining the distance between an affected

source and its maximum ground level concentration is generally 10 times the stack height in flat

terrain. However, the potential influence of terrain can impact the location and magnitude s of

significant concentration gradients. The following table shows each emission unit at an affected

facility, the stack height for the emissions unit, and the expected distance to the expected

maximum ground level concentration in flat terrain.

Table 3 .1

- 2 Calculated Distance for Maximum Concentration

ID Mesonet

Site Company/Facility Stack Stack Ht.

(ft) Distance

(km)

20 Hugo WFEC/Hugo Generating Station Unit 1 500 1.52

36 Porter OG+E/Muskogee Generating Station Unit 4 350 1.07

Unit 5 350 1.07

Unit 6 500 1.52

39 Redrock OG+E/Sooner Generating Station Unit 1 500 1.52

Unit 2 500 1.52

Since the maximum impact is expected to be between 0.5 km and 2 km, a domain of 10 km is

expected to be of sufficient size to determine the ambient air impacts from the affected sources

unless there is significant terrain. In domain s where there is significant terrain (Domain 36), the

domain w as extended to 15 km

.

3.2 How w ere the r eceptor g rids established ?

The model ing receptor grid is unique to the particular situation and i s dependent on the size of

the modeling domain, the number of modeled sources, and complexity of the terrain. For the

purposes of modeling f

or the 2010 1

- hour SO 2 designations, receptor placement differs since the

modeling is acting as a surrogate for monitoring. In areas where it is not feasible to place a

monitor (water bodies, etc.), receptors w ere not placed in th e se locations.

R eceptor placement w as of sufficient density to provide the resolution needed to detect

significant concentrations gradients, with receptors placed closer together near the source to

detect local gradients and placed farther apart away from the source. In addition, receptors w ere

placed at key locations s uch as existing monitoring sites (for comparison of modeled

concentrations to monitored concentrations) , sensitive locations (for determining impacts in

special areas), and along facility fence lines (the a mbient air boundary of the affected sources ).

T he total number of receptors var ies based on the specific domain and areas of maximum impact.

For the fine grid, a 100 meter spacing w as utilized. The receptor spacing increases as the

distance from the affe cted facilities increases. T he fine receptor grid was extend ed out far

enough to determine the maximum impact from the affected sources

. A fine grid extending out

to 2 km wa s used to identify the areas of maximum concentration based on the review of the

stack heights for the affected sources

. A generalized rectangular receptor grid for each domain

was generated using the following:Oklahoma 2010 SO 2 NAAQS Modeling Report Page 6

 R eceptors s paced at 100 m along the fence line of the affected sources;

 R eceptors spaced at 100 m from the fence line out to 2 km;

 R eceptors spaced at 250 m from 2 km out to 3 km;

 R eceptors placed at 500 m from 3 km to 5 km; and

 R eceptors spaced at 1 km from 5 km out to edge of domain (~ 10 km )

.

A e rial photos of the domain with the receptors are inc luded in Appendix A

.

Appendix W to 40 CFR Part 51 indicates maximum impacts occur on calm days as the plumes

encounter hills at or near the same height as the stacks. Terrain surrounding a facility w as

evaluated to determine if there we re hills in the ar ea at or above stack height and the domain w as

extend ed to include the se areas

. When high impacts are determined in these areas

, a fine grid

w as placed over the m to determine the maximum impact.

3.3 What t errain d ata w as u tilized for the modeling analyses ?

Terrain data was included in all 2010 1

- hour SO 2 designations modeling analyses. Terrain data

was obtained from the USGS Seamless Data Server at http://viewer.nationalmap.go v/viewer/

. The 1/3 arc

- second NED data w as obtained in the GeoTIFF format for use in AERMAP.

Interpolation of receptor and source heights from the 1/3 arc

- second NED elevation data w as

based on the current AERMAP guidance in Section 4.4 of the User’s Guide for the AERMOD

Terrain Preprocessor (AERMAP) (EPA

- 454/B

- 03

- 0003, 10/2004). AERMAP uses a distance

weighted bilinear interpolation method.

Oklahoma has three UTM zones (zones 13, 14, and 15). None of the modeling domain s for the

affected source s crosse d a UTM zone. All coordinates w ere based on the North American

Datum (NAD) 1983 (NAD83).

3.4 What we re the d omain c lassifications : r ural or u rban ?

Dispersing plumes encounter more turbulence in urban areas than in rural areas due to building

wakes as well as warmer temperatures. The higher dispersion in urban areas causes plume s to

spread more rapidly

. The areas of maximum impact i n urban areas occ ur closer to the source.

Determination of whether or not the domain of an affected source should be classified as urban

or rural w as b ased mainly on land use (the p referred method)

. However, the urban heat island

affect was reviewed for those affected sou rces located in metropolitan areas (OG&E Muskogee)

. D eterminations of the domain classification are shown below.

Table 3.4

- 1 Domain Classifications

ID Mesonet Site Company/Facility Urban/Rural

20 Hugo WFEC/Hugo Generating Station Rural

36 Porter OG+E/Muskogee Generating Station Rural /Urban

39 Redrock OG+E/Sooner Generating Station Rural

A e rial photos indicating the area surround ing the facility are included in Appendix B

.Oklahoma 2010 SO 2 NAAQS Modeling Report Page 7



### 4. WHAT SOURCE DATA W AS USED IN THE MODELING

ANALYSIS?

4. 1 What are the a ffected s ource c onfigurations and s ource t ypes ?

Accurate characterization of the affected sources is critical to air quality characterization

utilizing modeling. All of the affected sources are point sources. S tack parameters and facility

d ata (building and fence line data) w ere submitted by each affected facility. The facility data

was then reviewed and checked for consistency with emission inventory data and aerial images

including location (i.e. latitude and longitude or Universal Transv erse Mercator (UTM)

coordinates and datum) of the emission unit stacks relative to the nearby buildings or structures.

Aerial photos indicating the facility data superimposed onto the aerial photos are included in

Appendix C

.

4

. 2 What n earby s ources were i ncluded in the m odel ing d omains?

When determining which sources should be included in the modeling domains for each affected

source all nearby sources w ere evaluated. Nearby sources a re those sources that are within 20 km of

the affected sources and that could cause or contribute to a NAAQS violation in the vicinity of the

affected source

. All natural gas fired sources w ere excluded from the 2010 1

- hour SO 2 designations

modeling analyses because of the following:

 They do not cause a significant conc entration gradient ;

 They are not expected to cause or contribute to a NAAQS violation ;

 They are represent ed via the background concentrations

.

A ll other sources of SO 2 w ere included in the 2010 1

- hour SO 2 designations modeling analyses

. A

list of all sou rces in the nearby source inventory for each domain is included in Appendix D

.

4

. 3 How w ere i ntermittent e mission s ources addressed ?

For area designations under the 2010 1

- hour SO 2 primary NAAQS

, modeling of intermittent

emissions sources, such as emergency generators and limited intermittent startup/shutdown emissions

w ere not included based on the recommendations in the March 1, 2011 memorandum “Additional

Clarification Regarding Application of Appendix W Modeling Guidance for the 1

- hour NO 2 National

Ambient Air Quality Standard.”

4

. 4 What are the a ffected s ource e missions i nputs ?

For the 2010 1

- hour SO 2 designations , modeling can be used as a surrogate to ambient

monitoring to characterize air quality for the designations process. Because designations are

intended to address current actual air quality ( i.e. , modeling simulates a monitor)

, SO 2 designation modeling w as based on modeling of actual emissions data. Also, since the standard

is based on a 3 year average, m odeling for air quality designations w as based on the most recent

3 years of actual emissions using concurrent meteorological data

. Modeling of 3 years of actual

emissions with concurrent meteorolog ical data is the best represent ation of the impacts that

would be monitored in a 3

- year monitoring data set

.Oklahoma 2010 SO 2 NAAQS Modeling Report Page 8

4

. 4

. 1 How w ere h ourly e missions from the a ffected s ources determined?

Actual emission data for input into AERMOD w as generated for each affected s ource. Most

electric generating units (EGU) have continuous emissions monitoring systems (CEMS). In the

absence of CEMS data, simply dividing the annual emissions by the number of hours in the year is

not an accurate representation of actual emissions

. For affected sources without CEMS data, actual

emissions w ere based on actual throughputs and the calculated SO 2 emissions generally based on

a mass balance. F or sources that vary their operation throughout the year, AERMOD input variables

w ere used to re present their actual operation throughout the year. Use of AERMOD input variables

such as hour of day (HROFDY), hour of day and day of week (HRDOW), and monthly hour of day

and day of week (MHRDOW) w ere utilized to represent actual operation for those sou rces without

CEMS data. Varying emissions w ere based on the available information such as production logs,

fuel usage information, operating schedules, etc. CEMS data w as used to generate hourly

emissions files for the affected sources using the followin g methodology:

Step 1: T he emission data was downloaded from the Clean Air Markets Database (CAMD).

Step 2 : T he monthly data was combined generating annual emission data files for each source at

an affected facility with CEMS data

. Step 3 : The three variables used in an hourly emission file are emissions

, velocity, and

temperature. These hourly values we re generated from the CAMD datasets and

formatted into the units used by AERMOD. The emissions we re converted from lb/hr

values into g/s. The heat input given in the CAMD data was used with Method 19, CO 2 concentration, moisture concentration

, and stack temperature from recent relative

accuracy test audit s ( RATA ) , to generate the flow rate and resultant velocity. If a unit

wa s operating it was assig ned the normal stack temperature.

Step 4 : The data wa s then reviewed for continuity and for missing data. If there was a single

hour of missing data

, it was replaced with the average of surrounding non

- missing hours

. If there are periods of missing data with more than a single missing value, operational

data from the affected facility was reviewed to fill the missing hours.

4. 4 .2 What operational data was used from the RATA?

The stack parameters used to generate t he hourly emission file for AERMOD from the RATA

are listed below. The values are based on the average of all values recorded during the RATA.

Table 4.3.2

- 1 Operational Stack Data from RATA

Stack Temp % Moisture % CO 2

Station Unit 2012 2013 2014 2012 2013 2014 2012 2013 2014

Hugo Unit 1 313 323 292 11.75 11.80 12.01 12.15 11.81 11.22

Muskogee Unit 4 336 327 320 12.46 13.30 13.51 11.90 11.40 11.76

Unit 5 311 313 315 11.48 12.19 12.00 11.50 11.32 11.40

Unit 6 299 290 294 11.63 11.89 12.46 11.40 11.67 11.48

Sooner Unit 1 305 315 320 10.81 11.11 12.60 11.56 11.20 11.72

Unit 2 312 290 301 11.24 10.47 10.23 11.38 11.70 11.95Oklahoma 2010 SO 2 NAAQS Modeling Report Page 9

4

. 5 How w as GEP s tack h eight addressed?

Good Engineering Practice (GEP) stack height is the minimum stack height needed to prevent

the stack exhaust plume from being entrained in the wake of nearby obstructions. F or the 2010

1

- hour SO 2 NAAQS designations process

, actual stack heights w ere used for modeling actual

emissions rather than follow ing the GEP stack height policy . The GEP stack height policy use s

GEP stack height for stack heights exceeding GEP and actual stack height for stacks below GEP.

The use of actual stack heights in the modeling analysis mo re closely represent s a ctual ambient

ai r quality conditions from the affected sources

. Because the purpose of the 2010 1

- hour SO 2 NAAQS designation modeling is to act as a surrogate for monitoring

, i f a monitor were located

in the area around the affected source s , the concentrations detected a t the monitor would be

reflective of the effect of emissions from the actual stack heights of influencing sources.

4. 6 Wa s b uilding d ownwash included in the modeling analyses?

When one or more structures interrupt the wind flow, an area of turbulence call ed building

downwash is created. Pollutants emitted at a fairly low level (e.g., a roof, vent or short stack)

can be caught in this turbulence, affecting their dispersion. Modeling that includes calculations

for building downwash gives a more accurate re presentation of pollutant impact s than does

modeling that omits consideration of downwash e ffects.

A building is any physical obstruction to airflow at the modeled facility. A structure is a

building or group of buildings determined to be important in do wnwash considerations. The

dominant downwash structure is the structure that renders the highest GEP recommended stack

height. If a stack is at GEP or higher, then downwash is not a factor. GEP stack height is

calculated according to the following equat ion.

where: H = Recommended stack height.

h = The distance from the highest point on a tier or building to ground level.

L = The lesser of the height or projected width for a particular tier or structure.

Not only are accurate stack parameters important but so are accurate building parameters

. Building parameters include location and orientation relative to stacks and building size. Other

parameters include tier heights and coordinates. These parameters are input into BPIP

- PR IME to

calculate building parameters for AERMOD. Affected facilities have submitted information

regarding buildings located on their property. This data w as reviewed and included in the

modeling analyses.



### 5. WHAT METEOROLOGICAL DATA W AS USED IN THE

MODELING ANALYSIS?

5

. 1 What m eteorological d ata w as used?

2012

- 2014 meteorological data was utilized for the 2010 1

- hour SO 2 primary NAAQS

designations modeling. The S tate of O klahoma utilizes Oklahoma Mesonet surface data, alongOklahoma 2010 SO 2 NAAQS Modeling Report Page 10

with Nation al Climatic Data Center (NCDC) Integrated Surface Hourly Database (ISHD) surface

data and National Oceanic and Atmospheric Administration (NOAA) Earth System Research

Laboratory (ESRL) Global Systems Division (GSD) formerly Forecast Systems Laboratory

(FSL ) Upper Air (UA) data, with all air dispersion modeling. Oklahoma Mesonet data is

incorporated to help make more accurate forecasts of ambient impacts from the affected sources.

Use of the Oklahoma Mesonet data also promote s use of more recent, more accur ate, and more

representative data

. Processed Oklahoma Mesonet surface data is combined with ISHD surface

data and ESRL UA radiosonde data using AERMET to produce the surface and profile files used

by AERMOD. However, if the ISHD station is closer to the facility being modeled and the

station is an ASOS station with sub

- hourly observations, Mesonet data is not utilized with the

modeling since the ISHD surface data would be more representative.

5

. 2 What surfac e data w as used?

For each affected source domain a specific meteorological data set was developed based on

spatial and climatological (temporal) representativeness. The representativeness of the specific

meteorological data set to the affected source domain was based mainly on p roximity and t errain

. Representativeness of the surface characteristics (albedo, Bowen ratio, and surface roughness)

w ere also reviewed when assigning a specific metrological data set to an affected so urce domain.

5

. 2 .1 How were sites from the ISH D e valuated ?

The re are approximately 83 ISHD automated weather stations in and around Oklahoma that were

evaluated for combining with Oklahoma Mesonet data to accurately represent the individual

modeling domai ns

. These stations usually take atmospheric measurements once every hour.

The ISH data files were downloaded from the NCDC ISHD web site:

ftp://ftp.ncdc.noaa.gov/pub/data/noaa

. Some of the sites are ASOS stations with continuous sub

hourly values.

The ISH data sites were reviewed for completeness by evaluating the number of hours that were

recorded at each site. If a specific site contain ed a significant amount of missing hou rs , then

those specific sites were not considered when assigning ISH sites to specific Oklahoma Mesonet

sites. Since data from the Oklahoma Mesonet is combined with the ISHD data, there is generally

no need to replace missing values for individual variabl es

. O ne of the main variable s utilized

from the ISH data is cloud cover (GF1) . For each ISHD data file, the specific number of missing

cloud cover values was also evaluated

. If a specific site had a significant number of m issing

cloud cover values

, it w as also excluded

.

5

. 2 .1 .1 W as AERMINUTE utilized in the modeling analysis ?

The NCDC began archiving 1

- minute ASOS wind data (TD

- 6405), beginning January 2000 for

first

- order NWS ASOS stations, and beginning March 2005 for all other ASOS stations. For

th o se ASOS sites , AERMINUTE data w as used to incorporate continuous sub

- hourly wind data

. The ASOS (6405) files were downloaded and then processed using AERMINUTE. The ASOS

1

- minute files w ere download ed from http://www1.ncdc.noaa.gov/pub/data/ for each year and

applicable ASOS station

. There w ere two ASOS site s (KMKO and KSWO ) near the affected

facilit ies (OG&E Muskogee and OG&E Sooner) with sub

- hourly data.Oklahoma 2010 SO 2 NAAQS Modeling Report Page 11

5

. 2 .2 What is Oklahoma Mesonet d ata and how is it used ?

The Oklahoma Mesonet is a world

- class network of meteorological monitoring stations

. The

Oklahoma Mesonet is unique in its capability to measure a large variety of meteorological

conditions at so many sites across an area as large as Oklahoma. Oklahoma M esonet data i s

provided courtesy of the Oklahoma Mesonet, a cooperative venture between Oklahoma State

University (OSU) and t he University of Oklahoma (OU) and supported by the taxpayers of

Oklahoma. At each site, the meteorological conditions are continu ously measured and packaged

into 5

- minute observations

. These 5

- minute observations from the Oklahoma Mesonet we re

processed into a n AERMET acceptable format. No missing data interpolation was performed for

the 5

- minute data sets.

Specific NCDC ISHD dat a sites and ESRL UA rawinsonde observation (RAOB) data sites were

assigned to each Oklahoma Mesonet site based on distance and representativeness. Appendix E

list s the Oklahoma Mesonet sites used in the ambient air quality analyses and the assigned

NCDC I SHD data site and ESRL UA RAOB data site for each Oklahoma Mesonet site. Since

the NCDC ISHD Station KMKO was closer to the Muskogee modeling domain and is more

representative than the closest Mesonet Station (Porter) only data from the NCDC ISHD Station

was utilized when modeling the Muskogee area. Wind roses for the specific domains are

contained in Appendix F

.

5

. 3 What u pper a ir d ata w as u sed?

The ESRL operates nine RAOB weather stations in and around Oklahoma. These stations

usually take soundings twice a day. The ESRL data files we re downloaded from the ESRL

RA O B web site: http://esrl.noaa.gov/raobs/

.

The UA data was reviewed for missing soundings. A single missing sounding will cause a

whole day (24 h ours) of missing meteorological data values. To reduce the number of missing

meteorological data, replacement soundings were substituted for the missing soundings. The

replacement soundings were selected from a site with similar thermodynamic profiles. Each UA

data station was assigned a primary and a secondary replacement UA station. The primary

station is basically the station that i s closest to the station being reviewed. Each replacement

sounding was documented.

5

. 4 How w ere s urface c haracteristic s of the m eteorological s ites d etermined?

When using AERMET

, to prepare the meteorological data for AERMOD, three surface

characteristics ( Albedo, Bowen Ratio, and Surface Roughness Length ) must be determined for

each surface site . A lbedo is the fraction of total incident solar radiation reflected by the surface

back to space without absorption. Bowen ratio, an indicator of surface moisture, is the ratio of

sensible heat flux to latent heat flux. Surface roughness length relate s the height of obstacles t o

the wind flow and is an important factor in determining the magnitude of mechanical turbulence

and the stability of the boundary layer. Albedo and Bowen Ratio are used for determining

planetary boundary layer parameters for convective conditions driven by the surface sensible

heat flux.

AERSURFACE uses land cover data from the U.S. Geological Survey (USGS) National Land

Cover Data 1992 archives (NLCD92) to determine the land cover types for a specified location.Oklahoma 2010 SO 2 NAAQS Modeling Report Page 12

AERSURFACE matches the NLCD92 land cover categories to seasonal values of Albedo,

Bowen Ratio, and Surface Roughness and then calculates the surface characteristics for input

into AERMET. NLCD92 data in GeoTIFF format was downloaded from the Multi

- Resolution

Land Characteristics (MRLC) Consortiu m at the following link: http://www.mrlc.gov/viewerjs/

. The surface characteristics of the individual domains are included in Appendix G

.

5

. 4 .1 What was u sed to d etermin e the s urface m oisture c onditions?

The monthly rainfall since establishment of the Mesonet program (approximately 20 years) has

been analyzed for each Mesonet site. The surface moisture conditions (Average, Wet, Dry) for

each of the Oklahoma Mesonet stations for each month were then determined using the monthly

rainfall amounts compared to the average rainfall. These determinations were based on the

guidance contained in the AERSURFACE Users Guide. T he Bowen Ratio was then assigned

based on the monthly surface moisture conditions for each Oklahoma Mesonet station

.



### 6. WHAT BACKGROUND MONITORING DATA W AS USED IN THE

MODELING ANALYS E S?

6

. 1 Wha t b ackground m onitoring d ata is u tilized?

Background concentrations were added to 2010 1

- hour SO 2 designations modeling analyses

. Monitoring data was obtained from the EPA air data web site:

http://www .epa.gov/air/data/index.html

. Background concentrations w ere based on the most

recent complete year(s) of available monitoring data in the form of the standard indicated below.

Only data meeting the minimum data collection requirements or the minimum perc ent

observations w ere used when determining the design value s

.

Pollutant Averaging Period Basis of Design Value

SO 2 1

- hour 3 year average of 99 th Percentile 1

- hour daily maximum

The inclusion of ambient monitored background concentrations in the model results is important

in determining the projected cumulative impact of the affected source s and other contributing

nearby sources impacts. A uniform monitored background concentrati on based on the monitored

design values for the latest 3

- year period w as based on a “regional site” (i.e., a site t hat is located

away from the area s of interest but is impacted by similar natural and distant man

- made sources).

All of the monitoring sites in the state of Oklahoma and their related design concentrations are

shown below.

Table 6.1

- 1 2012

- 2014 Monitoring Design Values

Monitor ID County Latitude Longitude Conc.

μg/m 3

40

- 001

- 9009 Adair 35.75074

- 94.66970 39.5

40

- 071

- 0604 Kay 36.69727

- 97.08130 99.5

40

- 101

- 0167 Muskogee 35.79313

- 95.30220 129.2

40

- 109

- 1037 Oklahoma 35.61413

- 97.47510 9.6

40

- 143

- 0175 Tulsa 36.14988

- 96.01170 100.4Oklahoma 2010 SO 2 NAAQS Modeling Report Page 13 40

- 143

- 0179 Tulsa 36.15483

- 96.01580 72.0

40

- 143

- 0235 Tulsa 36.12695

- 95.99890 46.3

40

- 143

- 1127 Tulsa 36.20490

- 95.97650 36.0

All of the monitoring sites are impacted by large SO 2 sources except for the monitor located in

Oklahoma County. The monitors in Tulsa County are impacted by the Holly Tulsa Refinery and

the PSO Northeast Power Station. The Monitor located in Muskogee County is impacted by the

OG&E Muskogee Generating Station and the Georgia Pacific Muskogee Mill. The monitor in

Kay County is impacted by the Phillips 66 Ponca City Refinery. The monitor in Adair County is

impac ted by the Flint Creek Power Plant. Therefore, the impacts from the Oklahoma County

monitor were used to represent background impacts from area sources for all modeling domains.



### 7. WHAT A RE THE MODELED FACILITY IMPACTS?

7.1 What were the modeled impact s for the domain which included the WFEC Hugo

Generating Station?

The table below shows the results of the air quality analysis for the WFEC Hugo Generating

Station. The results of the modeling are the three year average of the highest fourth highest

(H4H) daily maximum impact or the three year average of the 99 th percentile daily maximum

impact

. The three year average of the H4H daily maximum impact for each of the facilit ies

included in the modeling analysis are also listed to show the impacts from each facility on the

modeling domain. However, the impacts listed d o not occur at the same location or at the same

time as the maximum impact

.

Table 7 .1

- 1 Domain 20 Modeling Impacts

Modeled Impact Background Total Impact

Domain Source Group (μg/m 3 ) (μg/m 3 ) (μg/m 3 )

D20 ALL 108.6 9.6 118.2

HUGO 108.5

IP 2.5

BDM 9.9

Based on the modeling review, the domain would be in compliance with the 2010 1

- hour SO 2 NAAQS of 75 pp b (196.4 μg/m 3 based on EPA Reference Conditions , 40 CFR §50.3 ).

7.2 What were the modeled impacts for the domain which included the OG&E

Muskogee Generating Station?

The table below shows the results of the air quality analysis for the OG&E Muskogee Generating

Station. The results of the modeling are the three year average of the H4H daily maximum

impact

. The three year average of the H4H daily maximum impact for each of the facilities

included in the modeling analysis are also listed to show the impacts from each facility on theOklahoma 2010 SO 2 NAAQS Modeling Report Page 14

modeling domain. However, the impac ts listed do not occur at the same location or at the same

time as the maximum impact.

OG&E is required by the Regional Haze Program to install BART on Unit 4 and Unit 5. OG&E

has committed to meeting the federal emission limit of 0.06 lb/MMBTU by Januar y 4 , 201 9 , by

conversion of Unit 4 and Unit 5 to natural gas. Since the conversion will occur sometime in the

future, the air quality analyses for this facility involved three operating scenarios

. The future

operating scenarios were modeled using continu ous operation of all the affected emission units.

For Scenario 1:

A ctual emissions fr om CEM data was used for OG&E Unit 4, Unit 5, & Unit 6;

For Scenario 2:

Modeled potential emissions from OG&E Unit 4 using the natural gas fired emission rate

of 0.0006 lb/MMBTU (which is lower than the BART emission limit of 0.0 6 lb/MMBTU) and

projected actual emissions from OG&E Unit 5 & Unit 6 using the 2013 and 2014 two year

average of the 99 th percentile emission rate and hea t input shown below . The emission rates and

heat input from 2012 w ere not used since t hey w ere not representative of future operation.

Table 7. 2

- 1 99 th Percentile Emission Factor & Heat Input for OG&E Muskogee Generating Station

2013 2014 Average

Unit lb/MMBTU MMBTUH lb/MMBTU MMBTUH lb/MMBTU MMBTUH

4 N/A 5,669 N/A 6,023 N/A 5,800

5 0.544 5,845 0.576 5,465 0.560 5,655

6 0.549 5,950 0.587 5,939 0.568 5,945

The emission factors and heat input used in the current permit to calculate emissions are listed

below. These emission factors and heat inputs are below those used for the modeling so the

emission s used in the modeling should be a conservative analysis of the future air quality

.

Table 7.2

- 2 Emission Factor s & Heat Input s Listed in Permit No. 2005

- 271

- TVR (M

- 7)

for OG&E Muskogee Generating Station

Unit lb/MMBTU MMBTUH

4 0.53 5480

5 0.51 5480

6 0.53 5150

For Scenario 3:

Potential emissions from OG&E Unit 4 and Unit 5 using the natural gas fired emission

rate of 0.0006 lb/MMBTU (which is lower than the BART emission limit of 0.06 lb/MMBTU)

and projected actual emissions from OG&E Unit 6 using the 2013 and 2014 two year average of

the 99 th percentile emission rate and heat inp ut shown above were modeled. The emission rates

and heat input from 2012 w ere not used since they w ere not representative of future operation.Oklahoma 2010 SO 2 NAAQS Modeling Report Page 15

Since the only variable s in the domain for the different modeling scenarios were the emissions

related to the OG &E Muskogee Generating Station, only the overall domain impacts and the

impacts from the OG&E Muskogee Generating Station are listed for Scenario 2 and 3

.

Table 7.2

- 3 Domain 36 Modeling Impacts Scenario 1

Modeled Impact Background Total Impact

Domain Source Group (μg/m 3 ) (μg/m 3 ) (μg/m 3 )

D36 ALL 214.0 9.6 2 23.6

OGE 201.4

GEORG 120.1

DALTIA 1.4

BORAL 56.3

OWENS 49.4

GRDA 23. 5

USLIME 3. 5

Table 7.2

- 4 Domain 36 Modeling Impacts Scenario 2 (Potential Future Impacts)

Modeled Impact Background Total Impact

Domain Source Group Units (μg/m 3 ) (μg/m 3 ) (μg/m 3 )

D36 ALL 179.9 9.6 18 9.5

OGE ALL 168.7

Unit 4 0.2

Unit 5 115.3

Unit 6 77.6

Table 7.2

- 5 Domain 36 Modeling Impacts Scenario 3 (Potential Future Impacts)

Modeled Impact Background Total Impact

Domain Source Group Units (μg/m 3 ) (μg/m 3 ) (μg/m 3 )

ALL 120.1 9.6 129.7

OGE ALL 77.7

Unit 4 0.2

Unit 5 0. 2

Unit 6 77.6

Based on the modeling review, the domain would not be able to demonstrate compliance with

the 2010 1

- hour SO 2 NAAQS of 75 pp b (196.4 μg/m 3 based on EPA Reference Conditions ) for

Scenario 1

. However, the domain will be able to demonstrate compliance for Scenario s 2 and 3.

After analyzing the MAXDCONT output files for Scenario 1, it was determined that there were

113 potential violations at 62 receptors. There are 62 violations based on the H4H, 37 potential

violations based on the H5H, and 13 violations based on the H6H. There were no additional

violations after the H6H.

At all 62 receptors, OG&E Muskogee Generating Station was the single largest contributor with

some contributions from Georgia Pacific Muskogee Mill.Oklahoma 2010 SO 2 NAAQS Modeling Report Page 16

7.3 What were the modeled impacts for the domain which included the OG&E

Sooner Generating Station?

The table below shows the results of the air quality analysis for the OG&E Sooner Generating

Station. The results of the modeling provided are the H4H impact s . The maximum impacts for

each facility included in the modeling analysis are also listed to show the impacts from each

facility on the modeling domain. However, the impacts listed do not occur at the same location

or at the same time as the maximum impa ct.

OG&E is required by the Regional Haze Program to install BART on Unit 1 and Unit 2. OG&E

has committed to meeting the federal emission limit of 0.06 lb/MMBTU by January 4 , 201 9 , by

controlling Unit 1 and Unit 2 using flue gas scrubbing or by converti ng the units to natural gas.

Since the emission reduction will occur sometime in the future, the air quality analyses for this

facility i nvolved t hree operating scenarios.

For Scenario 1:

Actual emissions from CEM data was used for OG&E Unit 1 & Unit 2.

For Scenario 2:

Modeled potential emissions from OG&E Unit 1 using the BART emission limit (0.06

lb/MMBTU) and projected actual emissions from OG&E Unit 2 using the 2012 through 2014

three year average of the 99 th percentile emission rate and heat input shown below. The emission

factor for 2013 (0.54) was not used since it was not representative of future operation.

Table 7. 3

- 1 99 th Percentile Emission Factor & Heat Input for OG&E Sooner Generating Station

2012 2013 2014 Average

Unit lb/MMBTU MMBTUH lb/MMBTU MMBTUH lb/MMBTU MMBTUH lb/MMBTU MMBTUH

1 N/A 5,455 N/A 5,337 N/A 5,419 N/A 5,405

2 0.715 5,490

--- 5,311 0.708 5,234 0.712 5,345

For Scenario 3:

Potential emissions from OG&E Unit 1 and Unit 2 using the BART emission limit (0.06

lb/MMBTU) were modeled.

Since the only variable in the domain for the different modeling scenarios is the emissions

related to the OG&E Sooner Generating Station, only the overall domain impacts and the

impacts from the OG&E Sooner Generating Station are listed.

T able 7. 3

- 2 Domain 3 9 Modeling Impacts Scenario 1

Modeled Impact Background Total Impact

Domain Source Group (μg/m 3 ) (μg/m 3 ) (μg/m 3 )

D39 ALL 127.0 9.6 136.6

OGE 126.8

CONT 33.5

PHILLIPS 1.8Oklahoma 2010 SO 2 NAAQS Modeling Report Page 17

Table 7. 3

- 3 Domain 39 Modeling Impacts Scenario 2 (Potential Future Impacts)

Modeled Impact Background Total Impact

Domain Source Group Units (μg/m 3 ) (μg/m 3 ) (μg/m 3 )

D39 ALL 152.1 9.6 161.7

OGE ALL 151.8

Table 7. 3

- 4 Domain 39 Modeling Impacts Scenario 3 (Potential Future Impacts)

Modeled Impact Background Total Impact

Domain Source Group Units (μg/m 3 ) (μg/m 3 ) (μg/m 3 )

D39 ALL 33.9 9.6 43.5

OGE ALL 23.4

Based on the modeling review, the domain would be able to demonstrate compliance with the

2010 1

- hour SO 2 NAAQS of 75 pp b (196.4 μg/m 3 based on EPA Reference Conditions ) for

Scenario 1. In addition, the impacts for Scenarios 2 and 3 demonstrat e of compliance with the

2010 1

- hour SO 2 NAAQS . The impacts for Scenario 2 are higher than the impacts for Scenario

1 since the emissions are based on projected heat input for Unit 2 and projected lb/MMBTU

. Also, Scenario 2 represents continuous operation of both units.



### 8. WHAT IS THE SUMMARY OF THE MODELING RESUL T S?

8.1 What areas demonstrate compliance with the 2010 1

- hour SO 2 NAAQS using

modeling ?

The areas surrounding the WFEC Hugo Generating Station and the OG&E Sooner Generating

Station can demonstrate compliance with the 2010 1

- hour SO 2 NAAQS using the modeling

.

8.2 What areas do not currently demonstrate compliance with the 2010 1

- hour SO 2 NAAQS using modeling?

While the modeling air quality analysis u nder Scenario 1 for t he area surrounding the OG&E

Muskogee Generating Station does not demonstrate compliance with the 2010 1

- hour SO 2 NAAQS

, the m odeling air quality anal yses under Scenario s 2 and 3 do demonstrate compliance

with the 2010 1

- hour SO 2 NAAQS. The federally enforceable BART reductions reflected in

Scenarios 2 and 3 are to be achieved by January 4, 2019.

C urrent ambient monitoring data indicates compliance with the 2010 1

- hour SO 2 NAAQS . The

predicted impacts at the monitoring site using model ing do not correlate well with the ambient

monitoring data which raises questions regarding meteorological data representativeness

. Additional studies of the modeling analyses should be conducted to examine the issues related to

correlation of predicted modeling impacts and actual monitor impacts. Also, a dditional

meteorological data ( e.g. on

- site)

, which is more representative of the modeling domain

, should

be collect ed to generat e modeling which accurately represents the area impacted by the OG&E

Muskogee Generating Station

.Oklahoma 2010 SO 2 NAAQS Modeling Report Page 18

8.2.1 What area has potential impacts greater than the 2010 1

- hour SO 2 NAAQS

that were predicted under Scenario 1 for the OG&E Muskogee Generati ng Station?

The area with the modeled impacts greater than the 2010 1

- hour SO 2 NAAQS are encompassed

within a single Township (Township 15N , Range 1 9 E ) in Muskogee County . The two largest

SO 2 sources in Muskogee County are also located within this township. The two largest SO 2

sources in Muskogee County and the area with modeled impacts greater than the 2010 1

- hour

SO 2 NAAQS are contained within eight sections of Township 15N, Rage 19E: Sections 15 (NE

Corner), 16 (NW C orner), 2 1 , 2 2 , 2 7 , 2 8 , 33 (SW Corner), and 34 (SE Corner). The area with

predicted impacts greater than the 2010 1

- hour SO 2 NAAQS are contained within a small area

within two sections of Township 15N, Rage 19E: Section 15 ( 80% ) and Section 16 ( 20% )

.



### 9

. WHAT REFERENCES WERE USED?

 Additional Clarification Regarding Applicability of Appendix W Modeling Guidance for

the 1

- hour NO 2 NAAQS (March 1 , 201 1);

o http://www.epa.gov/ttn/scram/guidance/clarification/Additional_Clarifications_Appe

ndixW_Hourly

- NO2

- NAAQS_FINAL_03

- 01

- 2011.pdf

 Guidance Concerning the Implementation of the 1

- hour SO 2 NAAQS for the Prevention of

Significant Deterioration Program ( August 23, 2010 );

o http://www.epa.gov/region07/air/nsr/nsrmemos/appwso2.pdf

 Applicability of Appendix W Modeling Guidance for the 1

- hour S O 2 NAAQS (August 23,

2010);

o http://www.epa.gov/ttn/scram/guidance/clarification/ClarificationMemo_AppendixW

_Hourly

- SO2

- NAAQS_FINAL_08

- 23

- 2010.pdf

 SO 2 NAAQS Designations Modeling Technical Assistance Document (December 2013) ;

o http://www.epa.gov/oaqps001/sulfurdioxide/pdfs/SO2ModelingTAD.pdf

 Guidance for 1

- Hour SO2 NAAQS SIP Submissions (September 22, 2011);

o http://www.epa.gov/oaqps001/sulfurdioxide/pdfs/DraftSO2Guidance_9

- 22

- 11.pdf

 User’s Guide for the AMS/EPA Regulatory Model

- AERMOD

o http://www.epa.gov/ttn/scram/models/aermod/aermod_userguide.zip

.  User’s Guide for the AERMOD Meteorological Data Preprocessor ( AERMET )

o http://www.epa.gov/ttn/scram/7thco nf/aermod/aermet_userguide.zip

.  AERMINUTE User’s Instruction

o http://www.epa.gov/ttn/scram/7thconf/aermod/aerminute_14337.zip

.  AERSURFACE User’s Guide

o http://www.epa.gov/ttn/scram/7thconf/aermod/aersurface_userguide.pdf

.

## Appendix A

– Facility Domains with ReceptorsOklahoma 2010 SO 2 NAAQS Modeling Report Page A

- 1 

## WFEC

– Hugo Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report Page A

- 2 

## OG&E

– Muskogee Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report Page A

- 3 

## OG&E

– Sooner Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report



## Appendix B

– Land Use/Land Cover Aerial PhotosOklahoma 2010 SO 2 NAAQS Modeling Report Page B

- 1 

## WFEC

– Hugo Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report Page B

- 2 

## OG&E

– Muskogee Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report Page B

- 3 

## OG&E

– Sooner Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report 

## Appendix C

– Aerial Photo Overlaid With Facility DataOklahoma 2010 SO 2 NAAQS Modeling Report Page C

- 1 

## WFEC

– Hugo Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report Page C

- 2 

## OG&E

– Muskogee Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report Page C

- 3 

## OG&E

– Sooner Generating StationOklahoma 2010 SO 2 NAAQS Modeling Report 

## Appendix D

– Source DataOklahoma 2010 SO 2 NAAQS Modeling Report Page D

- 1 Domain 20 Source Data

Source ID Facility Easting Northing Elevation Stk Ht Stk Temp Velocity Stk Dia SO 2

(m) (m) (m) (ft) (°F) (fps) (ft) (lb/hr)

UNIT 1 WFEC

– Hugo 839782.8 3769894.6 147.1 500.0 260 47.00 26.0 2

, 391.03

PLT76 1 BDM Eng 834500.0 3780048.7 156.3 25.0 160 96.67 3.0 8.98

IPBRKBLR International Paper 859439.4 3768633.0 151.3 246.0 133 42.60 11.0 4.62

IPPRBLR International Paper 859435.2 3768628.3 151.2 296.0 439 88.80 14.5 8.55

IPNRFN International Paper 859499.9 3768626.1 152.5 296.0 439 88.80 14.5 32.60

IPLIMEKILN International Paper 859486.6 3768587.3 152.6 148.0 469 44.70 5.8 0.36

1

- Emissions from the plant were limited based on operational data from the facility. The emissions were limited using the Seasonal Hour Day of Week

emission factor command (SHRDOW). Emissions from this facility were limited to Spring, Summer, and Fall; Monday through Frid ay; between the

hours of 9 a.m. and 5 p.m. The actual average numbe r of hours operated from 2012

- 2014 were 5 50 hours per year with a maximum of 950 hours in a

single year

.Oklahoma 2010 SO 2 NAAQS Modeling Report Page D

- 2 Domain 36 Source Data

Easting Northing Elevation Stk Ht Stk Temp Velocity Stk Dia SO 2

Source ID Facility (m) (m) (m) (ft) (°F) (fps) (ft) (lb/hr)

UNIT 4 OG&E Muskogee 293116.7 3959729.8 156.2 350.0 264 44.96 24.0 2

, 010.98

UNIT 5 OG&E Muskogee 293172.0 3959739.3 156.8 350.0 264 41.80 24.0 1

, 912.21

UNIT 6 OG&E Muskogee 293240.4 3959757.7 157.0 500.0 264 55.01 21.5 2

, 206.57

DAL20 Dalitalia 284208.4 3953784.7 171.2 46. 3 1 30 29. 80 4.95 0.11

DAL23 Dalitalia 284164.9 3953711.7 170.8 4 6.0 1 30 45.0 8 2.70 0.05

DAL29 Dalitalia 284093.8 3953787.7 171.0 51. 3 1 30 24. 1 0 5.3 6 0.09

BORSCRUB Boral 282161.2 3951159.0 183.5 70.0 355 36.29 6.2 43.60

GPSTACK1 Georgia Pacific 292555.0 3956494.1 161.9 260.0 353 28.46 10.0 85.33

GPSTACK3 Georgia Pacific 292594.0 3956513.0 162.0 260.0 306 28.24 13.8 412.56

OBFURNA Owens Brockway 288620.7 3960596.6 179.6 150.0 918 29.16 5.3 9.30

OBFURNB Owens Brockway 288656.6 3960582.4 180.0 80.0 389 28.89 7.1 18.61

M1 US Lime 334096.8 3940641.2 203.6 150.0 266 57.09 5.3 20.31

K1 US Lime 334000.6 3940571.3 204.5 96.0 155 31.20 7.0 0.17

UNIT 1 GRDA 294138.0 4007357.0 189.5 504.0 300 68.14 20.0 2

, 881.26

UNIT 2 GRDA 294211.0 4007262.0 188.8 507.0 190 90.98 20.0 922.97Oklahoma 2010 SO 2 NAAQS Modeling Report Page D

- 3 Domain 3 9 Source Data

Easting Northing Elevation Stk Ht Stk Temp Velocity Stk Dia SO 2

Source ID Facility (m) (m) (m) (ft) (°F) (fps) (ft) (lb/hr)

Unit 1 OG&E Sooner 674572.1 4036106.8 286.1 500.0 264 60.05 20.0 2

, 012.10

Unit 2 OG&E Sooner 674497.9 4036137.0 286.2 500.0 264 59.04 20.0 1

, 841.85

TO4 Continental Carbon 672587.8 4059257.6 293.2 213.3 1817 159.90 7.0 447.12

TO12 Continental Carbon 672416.8 4059290.6 293.4 150.0 1671 109.00 11.5 629.15

TO3 Continental Carbon 672538.8 4059261.6 293.6 150.0 1601 104.00 9.5 340.00

NO.4FCC Phillips Refinery 671244.4 4062452.8 300.7 175.0 423 81.30 4.5 1.12

NO.5FCC Phillips Refinery 671146.1 4061061.4 307.0 175.0 147 46.30 8.5 8.24

FLARESP Phillips Refinery 671369.5 4060672.6 301.0 199.0 1832 65.30 3.0 1.02

FLARECC Phillips Refinery 670807.4 4061307.2 301.3 150.0 1832 65.60 2.5 10.63

FLAREEP Phillips Refinery 671187.6 4062248.4 296.1 245.0 1832 65.60 2.5 3.13

B0008 Phillips Refinery 670832.1 4061973.3 304.6 162.0 336 12.60 8.0 1.43

B9/B10 Phillips Refinery 670828.5 4062066.5 304.9 89.0 305 31.80 11.8 1.85Oklahoma 2010 SO 2 NAAQS Modeling Report



## Appendix E

– 201 2

- 201 4 Oklahoma Mesonet Sites & Associated ISH & ESRL StationsOklahoma 2010 SO 2 NAAQS Modeling Report Pag e E

- 1 Oklahoma Mesonet Sites & Associated ISH & ESRL Stations

STID NAME/City COUNTY LAT LONG ELEV SFCS LAT LONG ELEV USAF # UAS LAT LONG

HUGO Hugo Choctaw 34.0308

- 95.5401 175 KHHW 1 34.0314

- 95.5398 177.7 720559 FWD 32.80

- 97.30

PORT 2 Porter Wagoner 35.8257

- 95.5598 193 KMKO 35.6577

- 95.3658 183.5 723556 OUN 35.23

- 97.47

REDR Red Rock Noble 36.3559

- 97.1531 293 KSWO 36.1624

- 97.0893 293.8 723545 OUN 35.23

- 97.47

1

- K HHW started on 2/2012, replace d 2011 with data from KPRX.

2

- KMKO is closer to the Muskogee area and is an ASOS station with sub

- hourly wind data and is more representative of the Muskogee area. Therefore, the

PORT Mesonet data was not utilized in the modeling analyses.

Abbreviations

STID

– Oklahoma Mesonet Station ID;

LAT, LONG

– Latitude and Longitude in NAD83;

ELEV

– Elevation is in meters;

SFCS

– ISH Surface Station Call Identifier;

UAS

– Upper Air Station Call Identifier.Oklahoma 2010 SO 2 NAAQS Modeling Report 

## Appendix F

– Wind RosesOklahoma 2010 SO 2 NAAQS Modeling Report Page F

- 1 2012

- 2014 Hugo Wind RoseOklahoma 2010 SO 2 NAAQS Modeling Report Page F

- 2 2012

- 2014 KMKO Wind RoseOklahoma 2010 SO 2 NAAQS Modeling Report Page F

- 3 2012

- 2014 Porter Wind RoseOklahoma 2010 SO 2 NAAQS Modeling Report Page F

- 4 2012

- 2014 Red Rock Wind RoseOklahoma 2010 SO 2 NAAQS Modeling Report 

## Appendix G

– Surface CharacteristicsOklahoma 2010 SO 2 NAAQS Modeling Report Page G

- 1 Domain 20 S urface Characteristics

HUGO Albedo AVG Wet Dry Surface

Winter 0.18 0.81 0.43 1.95 0.022

Spring 0.15 0.40 0.26 1.12 0.039

Summer 0.18 0.53 0.32 1.37 0.142

Fall 0.18 0.81 0.43 1.95 0.142

KHHW

Winter 0.18 0.81 0.43 1.95 0.022

Spring 0.15 0.40 0.26 1.12 0.039

Summer 0.18 0.53 0.32 1.37 0.144

Fall 0.18 0.81 0.43 1.95 0.144

KPRX

Winter 0.18 0.72 0.40 1.91 0.016

Spring 0.14 0.34 0.22 1.04 0.023

Summer 0.19 0.47 0.29 1.31 0.039

Fall 0.19 0.72 0.40 1.91 0.032

KAQR 1

Winter 0.18 0.84 0.42 1.90 0.044

Spring 0.15 0.44 0.26 1.14 0.092

Summer 0.18 0.47 0.29 1.14 0.189

Fall 0.18 0.84 0.42 1.90 0.189

1

– 2011 RunOklahoma 2010 SO 2 NAAQS Modeling Report Page G

- 2 Domain 3 6 S urface Characteristics

Albedo AVG Wet Dry Surface

PORT

Winter 0.18 0.73 0.39 1.77 0.026

Spring 0.15 0.36 0.23 1.01 0.042

Summer 0.18 0.45 0.28 1.16 0.183

Fall 0.18 0.73 0.39 1.77 0.183

KMKO

Winter 0.18 0.72 0.41 1.94 0.016

Spring 0.14 0.33 0.22 1.03 0.023

Summer 0.19 0.50 0.30 1.42 0.037

Fall 0.19 0.72 0.41 1.94 0.031

0167

Winter 0.17 0.64 0.37 1.47 0.021

Spring 0.14 0.37 0.24 0.93 0.027

Summer 0.18 0.43 0.28 1.01 0.064

Fall 0.18 0.67 0.37 1.47 0.064Oklahoma 2010 SO 2 NAAQS Modeling Report Page G

- 3 Domain 3 9 S urface Characteristics

REDR Albedo AVG Wet Dry Surface

Winter 0.19 0.87 0.46 1.77 0.014

Spring 0.17 0.37 0.26 1.01 0.050

Summer 0.18 0.65 0.35 1.16 0.112

Fall 0.18 0.87 0.46 1.77 0.112

KSWO

Winter 0.19 0.91 0.48 2.00 0.017

Spring 0.16 0.47 0.31 1.18 0.051

Summer 0.18 0.63 0.37 1.54 0.095

Fall 0.18 0.91 0.48 2.00 0.095